My
research explores the computational basis of human cognition, considering
the abstract computational problems that people face every day, and examining
how people solve these problems. I am particularly interested in problems
of induction, which involve making inferences about the underlying structure
of observed data. Making the leap from data to structure is an essential
part of the acquisition and organization of knowledge, and the question
of how people do this makes contact with issues in philosophy of science,
machine learning, and statistics.

Currently,
I am focusing on two questions: how people reason about chance and causality,
and how the statistical properties of language influence cognition. My
work on chance and causality examines how people learn that causal relationships
exist, what makes something seem "random", how to measure the
strength of a coincidence, and how people predict the future. My work
on language involves using probabilistic generative models to extract
interesting structure from collections of documents, and using this structure
to make predictions about cognitive tasks. For example, one such model
allows us to identify the topics discussed in a set of documents, and
to predict associations between words (why you think "cat" when
I say "dog") from these topics. These techniques are related
to models of similarity and categorization, another of my interests.

Each
of these questions involves an interesting computational problem. Through
modeling and experimentation, I explore how people solve this problem.
Many of the computational problems that people face appear in other contexts.
For example, randomness and causality both involve problems that have
been studied extensively in computer science and statistics. An important
part of my research is making connections between cognitive science and
other computational disciplines. These connections go both ways: I use
concepts from statistics, artificial intelligence, machine learning, and
elsewhere in computer science in explaining human cognition, and I use
the cognitive capacities of people as inspiration to develop models and
tools that contribute to these other disciplines.